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With the introduction of Hyperion Profitability and Cost Management (HPCM), many organizations have recognized the power of this breakthrough solution to build sophisticated and powerful cost models. As such, HPCM has been successfully in use for several years, and in numerous cases, its use has been expanded.

Since the initial release of HPCM, Oracle has developed additional variations of HPCM to provide a full suite of capabilities in costing and profitability that can more specifically provide the right tool for the right job (RTRJ). These additional offerings include HPCM-Detailed Profitability and HPCM-Management Ledger, the latter of which is available either in the on premise version (HPCM-ML) or the cloud version – Profitability & Cost Management-Cloud Service (PCMCS). The original solution of HPCM is now referred to as HPCM-Standard Profitability (HPCM-Standard).

Edgewater Ranzal is the leading implementation services provider of Oracle and Hyperion EPM solutions and has extensive experience with Hyperion Profitability and Cost Management (HPCM). This experience has prompted the notion that given the multiple offerings that are now available, it is worthwhile to evaluate the applicability of the new solutions to an organization’s existing use cases and consider making a change where appropriate. In particular, Management Ledger offers benefits of flexibility and process simplification to warrant consideration of conversion of an HPCM Standard model to HPCM-ML or PCMCS. This article discusses that process.

Background

Since HPCM’s introduction, it has been seen that there is not necessarily a one-size-fits-all solution for the set of needs in cost allocations and profitability. All allocations fundamentally follow the basic formula, A = S x F x D/Sum(D) where A = the target Allocated amount, S = Source amount, F = Factor, i.e. percent of source amount to be allocated, often 100%, D = Driver quantity, and Sum(D) = Sum of Driver quantities across target values.

However, this fundamental formula is where similarities end and distinctions begin. The original solution, HPCM-Standard, is well suited for cases where highly complex allocation models are utilized. It is also well positioned where adherence to a highly-structured framework is sought, and it provides capability for highly detailed graphical tracing of allocations in the user interface.

Alternatively, Detailed Profitability, which can be deemed as the “heavy-lifter” of the offerings, requires that users define relatively simple allocation rules through a single allocation stage. However, in exchange for this concession, the solution can apply those rules across a wide range of dimensions and is able to do so at a very granular level of detail. Also referred to as “Microcosting,” this solution leverages source pools and rates applied to a high volume of transactions or near-transactions. Firms within industries such as consumer goods, transportation and distribution, retail banking, and healthcare are among those that may want to leverage this capability. This solution enables capture of variation in cost at the shipment, order, transaction, or encounter level of detail, and then aggregates those values to higher levels such as product, service, or customer for analysis.

The third offering, Management Ledger, combines aspects of both of the other two solutions, such as some of the metadata granularity of Detailed Profitability, along with the logic complexity of Standard. This enables users to define custom models with fewer restrictions on the framework and fewer limits on the level of detail required for reporting. Management Ledger is also flexible to accommodate future changes through its Rule Set/Rule sequencing construct. Subsequent allocation logic changes can be of a substantial nature, potentially up to a near redesign. Also, the rules building process itself is simplified in Management Ledger and it is one that aligns well with the intuition of finance users. Further, Oracle’s current strategic direction is with Management Ledger, most notably seen in the recent release of PCMCS.

What is the benefit of conversion?

Management Ledger offers several key capabilities that can improve, streamline, or otherwise address existing challenges in a Standard Profitability environment.

Management Ledger does not rely on a back-end staging table paradigm for data loading as does HPCM-Standard. Such reliance requires the availability of resources with the database skills required to support SQL interfaces to automate model processes, as well as to perform maintenance when metadata updates are made. For some user sites, the availability of these skills is limited.

Management Ledger is an ASO application. It is not subject to the metadata restriction faced when deploying the HPCM-Standard calculation cube, which is BSO, and is subject to reaching the maximum number of potential blocks due to metadata duplication. Since Management Ledger does not duplicate the dimensions, it makes reporting easier for end-users and can eliminate the need for a “simplified” HPCM reporting application that is often created in an implementation of HPCM-Standard.

Management Ledger does not require the use of pre-defined stages and an associated limit of three dimensions per stage as utilized in HPCM-Standard. This framework drove design decisions and influences future changes at certain user sites.

Management Ledger is flexible to accommodate new methods of allocating data. The presence of a dimension in an application allows for its selection and filtering without the need for re-design.

Management Ledger provides an interface that can be quickly learned by business users. Its set-up and maintenance simply requires the identification of sources, destinations, and the driver bases of allocations. Because it does not rely upon or require use of any specific methodology, existing Planning and HFM users can quickly learn the navigation and logic of Management Ledger. As shown below, the process for rules building in Management Ledger is straightforward.

With all of these potential benefits, there are also offsetting considerations. Management Ledger may require more maintenance than HPCM-Standard due to a higher number of allocation rules, which is required in order to enable parallel processing. Further, the graphical built-in traceability screen in Management may be considered by some as being less intuitive than the screen provided with HPCM-Standard. Therefore, not in every case where Management Ledger is seen as a useful fit, will the advantages over Standard Profitability be sufficient justification to undertake the time and effort of a conversion.

What are the criteria for undertaking a Management Ledger Conversion?

To help evaluate whether it is worthwhile to pursue migrating a Standard Profitability model to Management Ledger, the following questions can be asked:

Is there a major re-organization pending that is prompting a re-evaluation of the overall stages framework?

Will there be future changes in which new allocation processes are added, such as moving beyond organizational allocations to ones that include other dimensions such as product or customer?

Do changes in allocation methodologies occur often? Will business users be required to make these updates/changes and without the support of IT staff?

Are new scenarios such as What-If or Ad-Hoc planned and is there an interest in testing different allocation methodologies versus the existing live production models?

Are the theoretical limits associated with the Block Storage Outline (BSO) being approached?

Is the process for updating the Standard Profitability staging tables considered to be time consuming and/or is the automation for populating the staging tables viewed as complex or poorly understood?

Are there currently other Management Ledger models in the organization and is there a need or desire to achieve communization of platforms?

Is there an objective to move applications to the Cloud?

What are the steps to migrate?

If the answer to any of the above questions is yes, then there is a potential opportunity to convert a Standard Profitability model to Management Ledger. In such a case, a prototype to test the concept should be created. This prototype should be loaded with a sample of data and rules, typically for at least one POV, and calculated and validated. Though each situation will have unique requirements, the overall steps are as follows:

Migrate the Standard model to the same environment where the Management Ledger test will be built.

Run a calculation of the Standard model to obtain a benchmark performance time.

Create a new cube and database and copy the dimensions from the existing cube. A new Master application should be created and the dimensionality copied from the existing Standard Profitability Master application. This is so that the dimensionality from the calculation cube isn’t used, in order to avoid duplicate dimensions.

Copy the dimensions from the old to the new cube. Make Cube Outline Updates.

Change the NoMember dimension member in each dimension to NoDimensionName.

Determine the dimension for the Drivers, usually the DataType or Account dimension.

Add the drivers from the Measures dimension to the Account or a DataType dimension.

Should both Source and Target allocation details be required for reporting, dimensions may need to be duplicated or split, such as in a case with Initial Cost Pool and Final Cost Pool.

Create a new Management Ledger Profitability application that references the new cube.

Deploy the Management Ledger Essbase Calculation engine.

Choose and create a single POV to start.

Import data from the existing cube to the new one utilizing the various methods available such as free form loading without rules, structured loading with rules, spreadsheet add-ins such as SmartView or other tools such as FDM/FDMEE. Note: For PCMCS, flat files of dimensions and data are employed.

Document the allocation rules in a template.

Enter the allocation rules through the ML user interface.

Run Model Validation to check the new Rule Sets and Rules for errors before calculating.

Launch a calculation. Start with running a single rule.

Validate the Results. Progressively select more rules for successive calculation as rules are validated.

Adjust methods iteratively.

Create and update a report to demonstrate the validations to end-users as well as how the results are consumed.

Migrate, once validation is complete including acceptability of both the results values and the processing times.

Some thoughts on building allocation rules

Upon having a Management Ledger outline, the allocation rules from Standard should be constructed through the user interface. There should be an association between the Stages in a Standard model versus the Rule Sets in a Management Ledger. As a starting point, the Rule Set sequence flow should match the stages, though it may be found necessary to break the stages into multiple rule sets.

Once the rule sets are determined, the rules themselves should be documented in a template (Excel, Word, etc.) that is easy to manage and understand. The example that follows shows the dimensionality of the Source, Destination, Driver Basis, and Source Offset.

This template becomes part of the documentation of the prototype. Upon completion of the template, a user should build the rule sets and rules in the Management Ledger interface. One of the key benefits of Management Ledger is to reference parent level values in the assignment rules. This provides the ability to create many-to-many source-destination associations with few keystrokes. This not only saves time in initial set-up, but also makes the entire process data driven such that when new dimension members such as new accounts, cost centers, products, or customers are added, the allocation rules automatically accommodate them without the need for editing or updating. The ability to select at the parent level also reduces the need for automation routines of the types that are frequently created in Standard Profitability implementations, such as those used to update staging tables (Management Ledger does not have staging tables).

Users should start with referencing the highest-level parents to make the process as automated as possible. If performance becomes an issue, it may be necessary to reference mid or lower level parents. Rules should be tested iteratively, i.e. run individually and then in groups to validate both the answers and to track processing time.

If calculation times exceed requirements or expectations, then start moving references to lower level parents. Avoid going to children as that will increase maintenance in the future.

Validation Concepts

Use the Rule Balancing Report to validate the cost flow and confirm that allocations in and out match expectations. Users should also generate a set of SmartView queries from the control HPCM-Standard Model and compare those to a set of SmartView queries from the HPCM-ML prototype. Input and Stage amounts from HPCM-Standard should compare to Rule Set amounts in HPCM-ML, including checks that rule sets are using drivers correctly. Calculation time and performance should also be tracked and benchmarked.

Conclusion

The advent of HPCM Management Ledger in both the on premise and cloud-based versions provides organizations with an opportunity to consider their existing solution and whether a migration to Management Ledger is warranted. Multiple considerations must be evaluated in this decision, and a prototype-based assessment is recommended as part of the process. Edgewater Ranzal provides an Assessment service offering to assist organizations with this evaluation, as well as a subsequent implementation. With over twenty experienced full-time consultants across the Americas and EMEA, and with more than twenty-five successful HPCM projects delivered since 2009, Edgewater Ranzal is the leading Oracle partner in delivering all versions of HPCM. Its comprehensive multi-product delivery approach can incorporate other tools such as Planning, DRM, FDMEE, & OBIEE. These qualifications, along with its close relationship with Oracle Development, make Edgewater Ranzal the premier partner for client success.